# TONGYANG LI

# Welcome!

I am an assistant professor at the Center on Frontiers of Computing Studies, Peking University. Previously I was a postdoctoral associate at the Center for Theoretical Physics, Massachusetts Institute of Technology during 2020-2021. I received my Ph.D. degree from the Department of Computer Science, University of Maryland in 2020, and I received Bachelor of Engineering from the Institute for Interdisciplinary Information Sciences, Tsinghua University and Bachelor of Science from the Department of Mathematical Sciences, Tsinghua University, both in 2015.

My research investigates interdisciplinary subjects among quantum computing, machine learning, and theoretical computer science, with the focus on designing quantum algorithms for machine learning and optimization. I am also interested in performing quantum algorithms on current noisy, intermediate-scale quantum devices (NISQ).

# News

08/2024, my paper "Adaptive Online Learning of Quantum States" was accepted by Quantum.

07/2024, my paper "Complexity of Digital Quantum Simulation in the Low-Energy Subspace: Applications and a Lower Bound" was accepted by Quantum.

05/2024, my papers "Provably Efficient Exploration in Quantum Reinforcement Learning with Logarithmic Worst-Case Regret" and "Quantum Algorithms and Lower Bounds for Finite-Sum Optimization" were accepted by the 41st International Conference on Machine Learning (ICML 2024).

04/2024, my papers "Quantum Non-Identical Mean Estimation: Efficient Algorithms and Fundamental Limits" and "Efficient Optimal Control of Open Quantum Systems" were accepted by the 19th Conference on the Theory of Quantum Computation, Communication and Cryptography (TQC 2024).

04/2024, my paper "A Quantum Algorithm Framework for Discrete Probability Distributions with Applications to Rényi Entropy Estimation“ was accepted by the IEEE Transactions on Information Theory.

03/2024, my paper "SpacePulse: Combining Parameterized Pulses and Contextual Subspace for More Practical VQE" was accepted by the 61st Design Automation Conference (DAC 2024).

01/2024, I will serve as a PC member of TQC 2024. Please consider submitting your work there!

01/2024, my paper "Near-Optimal Quantum Algorithm for Minimizing the Maximal Loss" was accepted by the 12th International Conference on Learning Representations (ICLR 2024).

01/2024, I will serve as a PC member of QCTiP 2024. Please consider submitting your work there!

11/2023, my paper "Quantum Lower Bounds for Finding Stationary Points of Nonconvex Functions" was accepted as a talk at the 27th Conference on Quantum Information Processing (QIP 2024).

09/2023, my paper "Logarithmic-Regret Quantum Learning Algorithms for Zero-Sum Games" was accepted by the 37th Conference on Neural Information Processing Systems (NeurIPS 2023).

05/2023, my paper "On Quantum Speedups for Nonconvex Optimization via Quantum Tunneling Walks" was published at Quantum.

04/2023, my papers "Quantum Lower Bounds for Finding Stationary Points of Nonconvex Functions" and "Near-Optimal Quantum Coreset Construction Algorithms for Clustering" were accepted by the 40th International Conference on Machine Learning (ICML 2023).

11/2022, the full version of my paper "Sampling-based Sublinear Low-rank Matrix Arithmetic Framework for Dequantizing Quantum Machine Learning" was published at the Journal of the ACM (JACM).

11/2022, my paper "Quantum Algorithms for Sampling Log-Concave Distributions and Estimating Normalizing Constants" was accepted as a talk at the 26th Conference on Quantum Information Processing (QIP 2023).

11/2022, my paper "Hamiltonian simulation with random inputs" was accepted by Physical Review Letters.

11/2022, my paper "Quantum Multi-Armed Bandits and Stochastic Linear Bandits Enjoy Logarithmic Regrets" was accepted by the 37th AAAI Conference on Artificial Intelligence (AAAI 2023).

11/2022, my paper "Quantum State Preparation with Optimal Circuit Depth: Implementations and Applications" was accepted by Physical Review Letters.

10/2022, my paper "Quantum simulation of real-space dynamics" was accepted by Quantum.

09/2022, my paper "Quantum Speedups of Optimizing Approximately Convex Functions with Applications to Logarithmic Regret Stochastic Convex Bandits" was accepted by the 36th Conference on Neural Information Processing Systems (NeurIPS 2022).

09/2022, my paper "Quantum Algorithms for Sampling Log-Concave Distributions and Estimating Normalizing Constants" was accepted by the 36th Conference on Neural Information Processing Systems (NeurIPS 2022).

07/2022, I will serve as a PC member of QIP 2023. Please consider submitting your work there!

07/2022, I am an outstanding reviewer for ICML 2022 (top 10%).

06/2022, I gave a talk about "Quantum algorithms for nonconvex optimization: Escaping from Saddle Points and Beyond" at the 2022 IMS Annual Meeting.

12/2021, my paper "Hamiltonian simulation with random inputs" was accepted as a contributed talk at the 25th Annual Conference on Quantum Information Processing (QIP 2022).

12/2021, I will serve as a PC member of TQC 2022. Please consider submitting your work there!

12/2021, I will serve as a PC member of QCTIP 2022. Please consider submitting your work there!

10/2021, I gave a talk about "Quantum algorithms for convex and nonconvex optimization" at the INFORMS 2021 Annual Meeting. See my presentation here.

09/2021, our paper "Escape saddle points by a simple gradient-descent based algorithm" was accepted by the 35th Conference on Neural Information Processing Systems (NeurIPS 2021). Congratulations to Chenyi Zhang for having the first accepted paper at NeurIPS!

08/2021, our paper "Quantum algorithms for escaping from saddle points" was accepted by Quantum. Congratulations to both Chenyi Zhang and Jiaqi Leng for having the first publication in quantum computing research!

08/2021, I served as a PC member of AQIS 2021.

07/2021, I joined the Center on Frontiers of Computing Studies, Peking University as an assistant professor. PhD and postdoc applications are welcomed!

# Awards

2022, Outstanding Reviewer Award (top 10%), 39th International Conference on Machine Learning (ICML 2022)

2020, Top Reviewer Award (top 33%), 37th International Conference on Machine Learning (ICML 2020)

2018-2021, QISE-NET Triplet Award (the only awardee in theoretical computer science in Cohort One)

2018-2020, IBM PhD Fellowship (the only awardee in quantum computing in 2018)

2015-2017, Lanczos Fellowship and Dean's Fellowship, Joint Center for Quantum Information and Computer Science and Department of Computer Science, University of Maryland

2015, IIIS Excellent Graduates, Institute for Interdisciplinary Information Sciences, Tsinghua University (only 6 awardees in total)

2014, Yao Award (Recognition Prize), Institute for Interdisciplinary Information Sciences, Tsinghua University (highest award to undergraduate CS majors; only 10 awardees in total)

2011, Gold Medal, Chinese Mathematical Olympiad (Top 50 around China)